Project Summary Cells live in diverse environments, from the cells in our bodies to single-celled organisms surviving in the soil. In order to navigate these complex environments, cells must be able to sense and respond to a variety of signals. This is done through biological signaling pathways, consisting of sensors and interacting proteins, which process external signals and transmit information. My research program focuses on understanding how these biological networks transmit information about the environment to the activity of intracellular effectors, such as transcription factors, to generate an appropriate cellular response or state. Understanding this signal processing represents a key gap in our knowledge of how healthy and diseased cells make decisions in response to stimuli. Specifically, we ask (1) How do signaling networks transform extracellular signals into appropriate intracellular signals? and (2) How are intracellular signals interpreted by the cell to generate appropriate responses? My research uses Saccharomyces cerevisiae, or budding yeast, as a model organism for addressing these questions in biological signal processing. Budding yeast exists as a unicellular microbe and therefore must be exquisitely aware of its environment in order to survive and compete with neighboring cells. Our research is focused on understanding signaling specificity and kinetics in the mitogen-activated kinase (MAPK) pathways as well as transcription factor regulation in response to environmental stress. MAP kinase pathways are conserved from yeast to humans and control vital cellular processes including proliferation, differentiation, and stress response. Furthermore, we have developed and continue to develop exquisite tools for controlling and perturbing biological networks in Saccharomyces cerevisiae, making this an ideal system in which to address the aforementioned questions. We take a multi-pronged approach. We develop microfluidic and optogenetic tools to perturb signaling pathways and combine these perturbations with mathematical modeling to understanding how different properties of signaling pathways, including bandwidth and crosstalk, allow them to appropriately transform their input signals. Furthermore, we use these tools to drive dynamics of intracellular effectors, such as transcription factors, and ask how these different effector dynamics generate cellular responses.